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This paper develops a Bayesian-inspired checklist of critical questions designed to support probabilistic reasoning in legal contexts. Building on Mackor’s (2026) proposal, rather than requiring formal Bayesian models or numerical probabilities, the framework translates key Bayesian principles into a practical sequence of guided questions aimed at helping judges improve and structure their reasoning and avoid probabilistic fallacies. is intended to assist judges in structuring and critically reflecting on their reasoning, while helping to identify and avoid probabilistic fallacies.The framework addresses common reasoning errors discussed in the legal literature (see Dahlman, 2023), including base-rate neglect, inversion fallacies, false dichotomies, dependence neglect, convergence neglect, and link-skipping. Organised according to key stages of probabilistic reasoning, the checklist is designed as a flexible aid to judicial deliberation and self-evaluation rather than a formal decision-making model. It aims to promote transparency in reasoning, encourage explicit reflection on assumptions and evidential relationships, and support the critical evaluation of expert evidence. Future research will focus on empirical testing and further refinement of the framework.
